Risk of Nonarteritic Anterior Ischemic Optic Neuropathy in Patients Prescribed Semaglutide.

Importance: Anecdotal experience raised the possibility that semaglutide, a glucagon-like peptide 1 receptor agonist (GLP-1 RA) with rapidly increasing use, is associated with nonarteritic anterior ischemic optic neuropathy (NAION). Objective: To investigate whether there is an association between semaglutide and risk of NAION. Design, Setting, and Participants: In a retrospective matched cohort study using data from a centralized data registry of patients evaluated by neuro-ophthalmologists at 1 academic institution from December 1, 2017, through November 30, 2023, a search for International Statistical Classification of Diseases and Related Health Problems, Tenth Revision code H47.01 (ischemic optic neuropathy) and text search yielded 16 827 patients with no history of NAION. Propensity matching was used to assess whether prescribed semaglutide was associated with NAION in patients with type 2 diabetes (T2D) or overweight/obesity, in each case accounting for covarying factors (sex, age, systemic hypertension, T2D, obstructive sleep apnea, obesity, hyperlipidemia, and coronary artery disease) and contraindications for use of semaglutide. The cumulative incidence of NAION was determined with the Kaplan-Meier method and a Cox proportional hazards regression model adjusted for potential confounding comorbidities. Data were analyzed from December 1, 2017, through November 30, 2023. Exposures: Prescriptions for semaglutide vs non-GLP-1 RA medications to manage either T2D or weight. Main Outcomes and Measures: Cumulative incidence and hazard ratio of NAION. Results: Among 16 827 patients, 710 had T2D (194 prescribed semaglutide; 516 prescribed non-GLP-1 RA antidiabetic medications; median [IQR] age, 59 [49-68] years; 369 [52%] female) and 979 were overweight or obese (361 prescribed semaglutide; 618 prescribed non-GLP-1 RA weight-loss medications; median [IQR] age, 47 [32-59] years; 708 [72%] female). In the population with T2D, 17 NAION events occurred in patients prescribed semaglutide vs 6 in the non-GLP-1 RA antidiabetes cohort. The cumulative incidence of NAION for the semaglutide and non-GLP-1 RA cohorts over 36 months was 8.9% (95% CI, 4.5%-13.1%) and 1.8% (95% CI, 0%-3.5%), respectively. A Cox proportional hazards regression model showed higher risk of NAION for patients receiving semaglutide (hazard ratio [HR], 4.28; 95% CI, 1.62-11.29); P < .001). In the population of patients who were overweight or obese, 20 NAION events occurred in the prescribed semaglutide cohort vs 3 in the non-GLP-1 RA cohort. The cumulative incidence of NAION for the semaglutide vs non-GLP-1 RA cohorts over 36 months was 6.7% (95% CI, 3.6%-9.7%) and 0.8% (95% CI, 0%-1.8%), respectively. A Cox proportional hazards regression model showed a higher risk of NAION for patients prescribed semaglutide (HR, 7.64; 95% CI, 2.21-26.36; P < .001). Conclusions and Relevance: This study's findings suggest an association between semaglutide and NAION. As this was an observational study, future study is required to assess causality.

Advances in Neuroscience, Not Devices, Will Determine the Effectiveness of Visual Prostheses.

Background: Innovations in engineering and neuroscience have enabled the development of sophisticated visual prosthetic devices. In clinical trials, these devices have provided visual acuities as high as 20/460, enabled coarse navigation, and even allowed for reading of short words. However, long-term commercial viability arguably rests on attaining even better vision and more definitive improvements in tasks of daily living and quality of life. Purpose: Here we review technological and biological obstacles in the implementation of visual prosthetics. Conclusions: Research in the visual prosthetic field has tackled significant technical challenges, including biocompatibility, signal spread through neural tissue, and inadvertent activation of passing axons; however, significant gaps in knowledge remain in the realm of neuroscience, including the neural code of vision and visual plasticity. We assert that further optimization of prosthetic devices alone will not provide markedly improved visual outcomes without significant advances in our understanding of neuroscience.

Machine learning applications in epilepsy.

Machine learning leverages statistical and computer science principles to develop algorithms capable of improving performance through interpretation of data rather than through explicit instructions. Alongside widespread use in image recognition, language processing, and data mining, machine learning techniques have received increasing attention in medical applications, ranging from automated imaging analysis to disease forecasting. This review examines the parallel progress made in epilepsy, highlighting applications in automated seizure detection from electroencephalography (EEG), video, and kinetic data, automated imaging analysis and pre-surgical planning, prediction of medication response, and prediction of medical and surgical outcomes using a wide variety of data sources. A brief overview of commonly used machine learning approaches, as well as challenges in further application of machine learning techniques in epilepsy, is also presented. With increasing computational capabilities, availability of effective machine learning algorithms, and accumulation of larger datasets, clinicians and researchers will increasingly benefit from familiarity with these techniques and the significant progress already made in their application in epilepsy.

Hypermutable DNA chronicles the evolution of human colon cancer.

Intratumor genetic heterogeneity reflects the evolutionary history of a cancer and is thought to influence treatment outcomes. Here we report that a simple PCR-based assay interrogating somatic variation in hypermutable polyguanine (poly-G) repeats can provide a rapid and reliable assessment of mitotic history and clonal architecture in human cancer. We use poly-G repeat genotyping to study the evolution of colon carcinoma. In a cohort of 22 patients, we detect poly-G variants in 91% of tumors. Patient age is positively correlated with somatic mutation frequency, suggesting that some poly-G variants accumulate before the onset of carcinogenesis during normal division in colonic stem cells. Poorly differentiated tumors have fewer mutations than well-differentiated tumors, possibly indicating a shorter mitotic history of the founder cell in these cancers. We generate poly-G mutation profiles of spatially separated samples from primary carcinomas and matched metastases to build well-supported phylogenetic trees that illuminate individual patients' path of metastatic progression. Our results show varying degrees of intratumor heterogeneity among patients. Finally, we show that poly-G mutations can be found in other cancers than colon carcinoma. Our approach can generate reliable maps of intratumor heterogeneity in large numbers of patients with minimal time and cost expenditure.

Attenuated total reflection Fourier transform infrared spectroscopy for on-chip monitoring of solute concentrations.

We report a cost-efficient Attenuated Total Reflection Fourier Transform Infrared Spectroscopy (ATR-FTIR) method for monitoring concentrations of solutes in solutions flowing through microfluidic channels. The method allows rapid acquisition of spectra and enables chemical characterisation and concentration measurements that are independent of the flow rate of liquids. The method enables independent measurement of concentrations of solutes with distinct spectral features in mixed solutions. For the polymer solutes studied in the present work, the method has a sensitivity of at least 10 microM (0.01 wt%). We also propose the applicability of the method for the differentiation between dissolved and adsorbed amphiphilic species.